{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# draw\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "# basic handling\n",
    "import os\n",
    "import glob\n",
    "import pickle\n",
    "import numpy as np\n",
    "# audio\n",
    "import librosa\n",
    "import librosa.display\n",
    "import IPython.display\n",
    "# normalization\n",
    "import sklearn\n",
    "# nn\n",
    "import keras\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout, Activation, Flatten\n",
    "from keras.layers import Convolution2D, MaxPooling2D\n",
    "from keras.utils import to_categorical\n",
    "from keras.callbacks import LearningRateScheduler\n",
    "\n",
    "from keras import Sequential\n",
    "from keras.layers import Dense, Activation, Conv2D, MaxPooling2D, Flatten, Dropout\n",
    "from keras.layers import Input\n",
    "from keras.optimizers import SGD\n",
    "\n",
    "## 置音频截断长度 采样率*时间(s)\n",
    "def load_clip(filename):\n",
    "    x, sr = librosa.load(filename)\n",
    "    if len(x) < 88200:\n",
    "        x = np.pad(x,(0,88200-x.shape[0]),'constant')\n",
    "    else:\n",
    "        x = x[0:88200:1]\n",
    "#     x = np.pad(x,(0,5292000-x.shape[0]),'constant')\n",
    "#     4429992\n",
    "    return x, sr\n",
    "def extract_feature(filename):\n",
    "    x, sr = load_clip(filename)\n",
    "    mfccs = librosa.feature.mfcc(y=x, sr=sr, n_mfcc=40)\n",
    "    norm_mfccs = sklearn.preprocessing.scale(mfccs, axis=1)\n",
    "    return norm_mfccs\n",
    "## 取数据(集) 返回音频数据MFCC矩阵\n",
    "def load_dataset(filenames):\n",
    "    features, labels = np.empty((0,40,173)), np.empty(0)\n",
    "    cnt = 0;\n",
    "    cnt_all = len(filenames)\n",
    "    \n",
    "    for filename in filenames:\n",
    "        mfccs = extract_feature(filename)\n",
    "        features = np.append(features,mfccs[None],axis=0)\n",
    "        cnt+=1\n",
    "        if(cnt%100==0):\n",
    "            print([str(cnt)+' / '+str(cnt_all)+' finished'])\n",
    "#         labels = np.append(labels, filename.split('\\\\')[1].split('-')[1])\n",
    "        namelist = filename.split('/')\n",
    "        labels = np.append(labels, namelist[len(namelist)-1].split('-')[1])\n",
    "    return np.array(features), np.array(labels, dtype=np.int)\n",
    "def get_trainData(filenames):\n",
    "    data_x, data_y = load_dataset(filenames)\n",
    "    train_x,val_x,train_y,val_y = sklearn.model_selection.train_test_split(data_x,data_y,test_size=0.3,random_state=0)\n",
    "    train_x = train_x.reshape(train_x.shape[0],train_x.shape[1],train_x.shape[2],1)\n",
    "    val_x = val_x.reshape(val_x.shape[0],val_x.shape[1],val_x.shape[2],1)\n",
    "#     test_x = test_x.reshape(test_x.shape[0],test_x.shape[1],test_x.shape[2],1)\n",
    "\n",
    "    train_y = to_categorical(train_y)\n",
    "    val_y = to_categorical(val_y)\n",
    "#     test_y = to_categorical(test_y)\n",
    "    return train_x,val_x,train_y,val_y\n",
    "def get_testData(filename):\n",
    "    mfccs = extract_feature(filename)\n",
    "    mfccs = mfccs.reshape(mfccs.shape[0],mfccs.shape[1],mfccs.shape[2],1)\n",
    "    return mfccs\n",
    "def show_history(history):\n",
    "    print(history.history.keys())\n",
    "    fig = plt.figure(figsize=(20,5))\n",
    "    plt.subplot(121)\n",
    "    plt.plot(history.history['acc'])\n",
    "    plt.plot(history.history['val_acc'])\n",
    "    plt.title('model accuracy')\n",
    "    plt.ylabel('accuracy')\n",
    "    plt.xlabel('epoch')\n",
    "    plt.legend(['train', 'test'], loc='upper left')\n",
    "    plt.subplot(122)\n",
    "    plt.plot(history.history['loss'])\n",
    "    plt.plot(history.history['val_loss'])\n",
    "    plt.title('model loss')\n",
    "    plt.ylabel('loss')\n",
    "    plt.xlabel('epoch')\n",
    "    plt.legend(['train', 'test'], loc='lower left')\n",
    "    plt.show()\n",
    "## 构造卷积网络模型\n",
    "def initial(train_x,train_y):\n",
    "    model = Sequential()\n",
    "\n",
    "    # BLOCK 1\n",
    "    # model.add(Conv2D(filters = 64, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block1_conv1', input_shape = (40, 173, 1)))   \n",
    "    model.add(Conv2D(filters = 32, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block1_conv1', input_shape = train_x.shape[1:]))   \n",
    "    # model.add(Conv2D(filters = 32, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block1_conv2'))\n",
    "    model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2), name = 'block1_pool'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    # BLOCK2\n",
    "    model.add(Conv2D(filters = 64, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block2_conv1'))   \n",
    "    # model.add(Conv2D(filters = 64, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block2_conv2'))\n",
    "    model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2), name = 'block2_pool'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    # BLOCK3\n",
    "    model.add(Conv2D(filters = 128, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block3_conv1'))   \n",
    "    # model.add(Conv2D(filters = 128, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block3_conv2'))\n",
    "    # model.add(Conv2D(filters = 128, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block3_conv3'))\n",
    "    model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2), name = 'block3_pool'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    # BLOCK4\n",
    "    model.add(Conv2D(filters = 256, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block4_conv1'))   \n",
    "    # model.add(Conv2D(filters = 256, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block4_conv2'))\n",
    "    # model.add(Conv2D(filters = 256, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block4_conv3'))\n",
    "    model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2), name = 'block4_pool'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    # BLOCK5\n",
    "    model.add(Conv2D(filters = 512, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block5_conv1'))   \n",
    "    # model.add(Conv2D(filters = 512, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block5_conv2'))\n",
    "    # model.add(Conv2D(filters = 512, kernel_size = (3, 3), activation = 'relu', padding = 'same', name = 'block5_conv3'))\n",
    "    model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2), name = 'block5_pool'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    model.add(Flatten())\n",
    "    # model.add(Dense(1024, activation = 'relu', name = 'fc1'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    # model.add(Dense(1024, activation = 'relu', name = 'fc2'))\n",
    "    # model.add(Dropout(0.5))\n",
    "    model.add(Dense(10, activation = 'softmax', name = 'prediction'))\n",
    "\n",
    "    model.compile(optimizer='Adam',\n",
    "                    loss='categorical_crossentropy',\n",
    "                    metrics=['accuracy'])\n",
    "    model.summary(line_length=80)\n",
    "    return model\n",
    "## 输入训练数据train_x train_y 验证数据val_x val_y为通过调用load_dataset函数读取指定目录下的音频数据\n",
    "def train(model,train_x,train_y,val_x,cal_y):\n",
    "    history = model.fit(train_x, train_y, epochs=10, batch_size=32, validation_data=(val_x, val_y))\n",
    "    show_history(history)\n",
    "#     loss,accuracy=model.evaluate(test_x,test_y)\n",
    "#     print('loss:',loss)\n",
    "#     print('accuracy:',accuracy)\n",
    "def test(model,x):\n",
    "    result = model.predict(x)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['100 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['200 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['300 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['400 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['500 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['600 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['700 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['800 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['900 / 8732 finished']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:180: UserWarning: Numerical issues were encountered when centering the data and might not be solved. Dataset may contain too large values. You may need to prescale your features.\n",
      "  warnings.warn(\"Numerical issues were encountered \"\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/data.py:197: UserWarning: Numerical issues were encountered when scaling the data and might not be solved. The standard deviation of the data is probably very close to 0. \n",
      "  warnings.warn(\"Numerical issues were encountered \"\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-e1bbfc2c9f21>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0mlength\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_files\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m//\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0mval_files\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_files\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mrand_index\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mlength\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mtrain_x\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mval_x\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtrain_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mval_y\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_trainData\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_files\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0;31m# initial()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-3-e32c74823e04>\u001b[0m in \u001b[0;36mget_trainData\u001b[0;34m(filenames)\u001b[0m\n\u001b[1;32m     59\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_trainData\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilenames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m     \u001b[0mdata_x\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_y\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_dataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilenames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     62\u001b[0m     \u001b[0mtrain_x\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mval_x\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtrain_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mval_y\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msklearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel_selection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_test_split\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_x\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdata_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtest_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.3\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m     \u001b[0mtrain_x\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_x\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_x\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtrain_x\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtrain_x\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-3-e32c74823e04>\u001b[0m in \u001b[0;36mload_dataset\u001b[0;34m(filenames)\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfilename\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfilenames\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mmfccs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_feature\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0mfeatures\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmfccs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m         \u001b[0mcnt\u001b[0m\u001b[0;34m+=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-3-e32c74823e04>\u001b[0m in \u001b[0;36mextract_feature\u001b[0;34m(filename)\u001b[0m\n\u001b[1;32m     38\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mextract_feature\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m     \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_clip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     41\u001b[0m     \u001b[0mmfccs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlibrosa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeature\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmfcc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn_mfcc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m     \u001b[0mnorm_mfccs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msklearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpreprocessing\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscale\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmfccs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-3-e32c74823e04>\u001b[0m in \u001b[0;36mload_clip\u001b[0;34m(filename)\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0;31m## 置音频截断长度 采样率*时间(s)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mload_clip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m     \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlibrosa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     32\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m88200\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     33\u001b[0m         \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m88200\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'constant'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/librosa/core/audio.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(path, sr, mono, offset, duration, dtype, res_type)\u001b[0m\n\u001b[1;32m    147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    148\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0msr\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 149\u001b[0;31m         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr_native\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mres_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mres_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    150\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    151\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/librosa/core/audio.py\u001b[0m in \u001b[0;36mresample\u001b[0;34m(y, orig_sr, target_sr, res_type, fix, scale, **kwargs)\u001b[0m\n\u001b[1;32m    517\u001b[0m         \u001b[0my_hat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresample_poly\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_sr\u001b[0m \u001b[0;34m//\u001b[0m \u001b[0mgcd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morig_sr\u001b[0m \u001b[0;34m//\u001b[0m \u001b[0mgcd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    518\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 519\u001b[0;31m         \u001b[0my_hat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresampy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morig_sr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_sr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mres_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    520\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    521\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfix\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/resampy/core.py\u001b[0m in \u001b[0;36mresample\u001b[0;34m(x, sr_orig, sr_new, axis, filter, **kwargs)\u001b[0m\n\u001b[1;32m    111\u001b[0m     \u001b[0mx_2d\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mswapaxes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    112\u001b[0m     \u001b[0my_2d\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mswapaxes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 113\u001b[0;31m     \u001b[0mresample_f\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_2d\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_2d\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_ratio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minterp_win\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minterp_delta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprecision\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    114\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "## 设置GPU占用\n",
    "import tensorflow as tf \n",
    "from keras.backend.tensorflow_backend import set_session \n",
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "config = tf.ConfigProto() \n",
    "config.gpu_options.per_process_gpu_memory_fraction = 0.7 \n",
    "set_session(tf.Session(config=config))\n",
    "## 目录读取文件\n",
    "parent_dir = './data/UrbanSound8K/audio/'\n",
    "data_list = ['fold1/','fold2/','fold3/','fold4/','fold5/','fold6/','fold7/','fold8/','fold9/','fold10/']\n",
    "# train_dir = 'train/'\n",
    "val_dir = 'val/'\n",
    "test_dir = 'test/fold10/'\n",
    "\n",
    "file_name = '*.wav'\n",
    "data_files = []\n",
    "for data in data_list:\n",
    "    \n",
    "#     train_files = glob.glob(os.path.join(parent_dir, train_dir, file_name))\n",
    "    data_files = data_files + glob.glob(os.path.join(parent_dir, data, file_name))\n",
    "rand_index = np.argsort(np.random.uniform(0,1,len(data_files)))\n",
    "length = len(data_files)*4//10\n",
    "val_files = np.array(data_files)[rand_index[0:length:1]]\n",
    "train_x,val_x,train_y,val_y = get_trainData(data_files)\n",
    "# initial()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "________________________________________________________________________________\n",
      "Layer (type)                        Output Shape                    Param #     \n",
      "================================================================================\n",
      "block1_conv1 (Conv2D)               (None, 40, 173, 32)             320         \n",
      "________________________________________________________________________________\n",
      "block1_pool (MaxPooling2D)          (None, 20, 86, 32)              0           \n",
      "________________________________________________________________________________\n",
      "block2_conv1 (Conv2D)               (None, 20, 86, 64)              18496       \n",
      "________________________________________________________________________________\n",
      "block2_pool (MaxPooling2D)          (None, 10, 43, 64)              0           \n",
      "________________________________________________________________________________\n",
      "block3_conv1 (Conv2D)               (None, 10, 43, 128)             73856       \n",
      "________________________________________________________________________________\n",
      "block3_pool (MaxPooling2D)          (None, 5, 21, 128)              0           \n",
      "________________________________________________________________________________\n",
      "block4_conv1 (Conv2D)               (None, 5, 21, 256)              295168      \n",
      "________________________________________________________________________________\n",
      "block4_pool (MaxPooling2D)          (None, 2, 10, 256)              0           \n",
      "________________________________________________________________________________\n",
      "block5_conv1 (Conv2D)               (None, 2, 10, 512)              1180160     \n",
      "________________________________________________________________________________\n",
      "block5_pool (MaxPooling2D)          (None, 1, 5, 512)               0           \n",
      "________________________________________________________________________________\n",
      "flatten_2 (Flatten)                 (None, 2560)                    0           \n",
      "________________________________________________________________________________\n",
      "prediction (Dense)                  (None, 10)                      25610       \n",
      "================================================================================\n",
      "Total params: 1,593,610\n",
      "Trainable params: 1,593,610\n",
      "Non-trainable params: 0\n",
      "________________________________________________________________________________\n",
      "Train on 6112 samples, validate on 3492 samples\n",
      "Epoch 1/10\n"
     ]
    }
   ],
   "source": [
    "## 设置GPU占用\n",
    "import tensorflow as tf \n",
    "from keras.backend.tensorflow_backend import set_session \n",
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "config = tf.ConfigProto() \n",
    "config.gpu_options.per_process_gpu_memory_fraction = 0.3 \n",
    "set_session(tf.Session(config=config))\n",
    "\n",
    "train_x = pickle.load(open('./train_x.dat', 'rb'))\n",
    "train_y = pickle.load(open('./train_y.dat', 'rb'))\n",
    "val_x = pickle.load(open('./val_x.dat', 'rb'))\n",
    "val_y = pickle.load(open('./val_y.dat', 'rb'))\n",
    "test_x = pickle.load(open('./test_x.dat', 'rb'))\n",
    "test_y = pickle.load(open('./test_y.dat', 'rb'))\n",
    "train_x = train_x.reshape(train_x.shape[0],train_x.shape[1],train_x.shape[2],1)\n",
    "val_x = val_x.reshape(val_x.shape[0],val_x.shape[1],val_x.shape[2],1)\n",
    "test_x = test_x.reshape(test_x.shape[0],test_x.shape[1],test_x.shape[2],1)\n",
    "## 前18行代替上面运行结果\n",
    "train_y = to_categorical(train_y)\n",
    "val_y = to_categorical(val_y)\n",
    "test_y = to_categorical(test_y)\n",
    "model = initial(train_x,train_y)\n",
    "train(model,train_x,train_y,val_x,val_y)\n",
    "test(model,test_x)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
